Contents:

1. Asymptotic complexity, estimation of execution time of a code
2 .1D arrays and lists, prefix sum, binary search
3. 2D arrays and matrices
4. Strings and text files
5. Recursion I, principles, simple examples
6. Library data structures and functions for searching and sorting, their complexity
7. Python application libraries Numpy, Scipy, with examples of use
8. Python application libraries Matplotlib, SageMath, NetworkX, with examples of use
9. Abstract data structures -- stack, queue, tree, graph -- and their implementation
10. Recursion 2, tree processing
11. Graph processing and searching 1, graph representation, local search
12. Graph processing and searching 2, BFS DFS
13. Rezerva
14. Rezerva

Seminar contents:

1. Asymptotic complexity of Python code and code fragments
2. 1D array and list processing,Python built-in functions
3. Operations on matrices, 2D array as image or function domain
4. Text files processing, text search
5. Recursive functions and procedures. Recursive generation of data/objects
6. Effectivity of search and sort methods on various datasets
7. Scientific and math computations with Numpy and Scipy,
8. Data visualisation with Python libraries
9. Homework problems comments and consultations
10. Tree traversal, In-, Pre and Post-order, recursion tree of a function call
11. Comparing effectivity of graph representations.
12. BFS and DFS implementations
13. Rezerva
14. Rezerva

Recommended literature:

John V. Guttag: Introduction to Computation and Programming Using Python
Revised and Expanded Edition, The MIT Press, 2013.
https://doc.lagout.org/programmation/python/Introduction%20to%20Computation%20and%20Programming%20using%20Python%20%28rev.%20ed.%29%20%5BGuttag%202013-08-09%5D.pdf

John M. Zelle: Python Programming: An Introduction to Computer Science (Third Edition), Franklin, Beedle & Associates, 2016
http://mcsp.wartburg.edu/zelle/python/

Various authors: SciPy cookbook, 2015
https://scipy-cookbook.readthedocs.io/index.html

David Cournapeau: scikit-learn library 2007-2018
https://scikit-learn.org/stable/

Abbreviations used:

Semester:

• W ... winter semester (usually October - February)
• S ... spring semester (usually March - June)
• W,S ... both semesters

Mode of completion of the course:

• A ... Assessment (no grade is given to this course but credits are awarded. You will receive only P (Passed) of F (Failed) and number of credits)
• GA ... Graded Assessment (a grade is awarded for this course)
• EX ... Examination (a grade is awarded for this course)
• A, EX ... Examination (the award of Assessment is a precondition for taking the Examination in the given subject, a grade is awarded for this course)

Weekly load (hours per week):

• P ... lecture
• C ... seminar
• L ... laboratory
• R ... proseminar
• S ... seminar